Analytics and the Cloud Data Warehouse Imperative

Big data, big business, big gains

Big data is nothing new. In fact, it fell off the Gartner hype curve in 2015. That’s not to say that big data’s business appeal has in any way lessened, or the promise of big data is any less compelling. Whether measured in terabytes, petabytes, exabytes, zettabytes, or yottabytes, big data is getting bigger by the millisecond. The world will create 180 zettabytes of data (or 180 trillion gigabytes) in 2025, up from less than 10 zettabytes in 2015, according to IDC.

Deriving actionable insights – correlations, trends, outliers, etc. – in real time from terabytes of big data – operational, transactional, structured, unstructured – is vital to success for businesses of all sizes across all industries in today’s increasingly global, hyper-competitive, always-on, internet-of-everything business world.

Reporting – When data sets are predictable, or volumes of data are low, you can rely on traditional reporting methods and platforms. When you are looking for new insights, or want to  uncover a trend or correlation you didn’t already know, or dealing with millions or billions of rows, you need Analytics.

Analytics — predictive, historical, diagnostic, reporting, analysis (and other kinds) — are all the rage in business today, and for good reason. The unprecedented data available about both customers and business operations holds the key to not only strengthening customer loyalty and improving core operations, but also provides the drivers for unparalleled productivity gains, launching new business models and even upending entire industries.

The promise of big data is both compelling and straightforward — crunch large data volumes to unlock insights that inform timely decisions that boost efficiency, the bottom line, and competitiveness — which is why analysts are predicting big spending and big opportunities for big data analytics.

According to IDC, worldwide revenues for big data and business analytics will grow from $130.1 billion in 2016 to more than $203 billion in 2020, at a compound annual growth rate (CAGR) of 11.7%.

Moreover, IDC predicts that by 2020, organizations able to analyze all relevant big data analytics and deliver actionable intelligence will achieve an extra $430 billion in productivity benefits over their less-data-savvy peers.

The enormous value hidden in big data is well documented. McKinsey reports that retailers effectively tapping big data can increase operating margins by as much as 60%. Walmart used big data analysis to drive a 10–15% increase in completed online sales for $1 billion in incremental revenue. According to a survey conducted by MIT Sloan Management Review, top-performing organizations are twice as likely as lower-performers to apply analytics in their operations.

A cloud data warehouse for the digital era

Today’s IT landscape has become increasingly complex and costly, with companies investing millions of dollars designing, implementing, and maintaining multiple databases, data-marts, and enterprise data warehouses to accommodate the ever-increasing data volume generated by multiple ERP instances, numerous business applications (CRM, SRM, SCM, etc.), and the deluge of unstructured data from social media, web traffic, IoT, and other sources now streaming into enterprises.

Traditional on-premise databases and their massive disk farms are costly CPU hogs that pose daunting power and cooling challenges. Moreover, relational database management systems (RDBMS) are woefully inadequate for meeting today’s big data analytics and business reporting needs. While good at storing persistent, structured data, traditional RDBMS fail when it comes to quickly analyzing massive quantities of structured and unstructured data to inform critical, timely business decisions. In short, they take too long and consume too many computing resources.

The days of (latent) IT production reports pushed out to managers are quickly coming to an end. No one wants to wait for time-consuming batch processing when far too compelling are the advantages of real-time, fact-based decision-making capabilities powered by intuitive, self-service analytics/BI tools in the hands of marketing, sales, supply chain management, manufacturing, engineering, risk management, finance, HR, frontline workers, and line-of-business pros.

The increased need for quick business decisions has dramatically heightened the importance of business intelligence and real-time data analytics, both of which are increasingly dependent on advanced cloud-based data warehousing solutions.

The cloud data warehouse is a new and fundamentally different technology offering. Top drivers for adoption include cost savings and markedly faster and easier provisioning, administration, and monitoring. The increase in need for a dedicated storage system for a surge in volume (and variety) of data, rise in demand for column-oriented data warehouse solutions to perform advanced analytics, the need for low-latency, real-time viewing, and analytics on operational data are additional major factors that are driving global cloud data warehousing market growth.

Cloud-based data warehouses enable organizations to get a comprehensive view of their customer transactions and data, allowing various teams across the organization to quickly sort information and analyze it to drive customer engagement initiatives. With data stored in a single repository, organizations can easily ensure the privacy and security of their customer and transactional data, reducing the risks associated with failure to comply with various industry regulations and compliance requirements.

Most importantly, the cloud data warehouse is an elastic resource. You can scale it up and down (or turn it on and off), as needed. The cloud data warehouse also delivers rapid time-to-value: subscribers can be up and running in weeks, instead of months or years as with on-premises DW projects.

Of course, the security of data in the cloud is imperative, particularly when you consider the business-critical nature of a data warehouse. Even though security is an obvious concern, most cloud providers have watertight security features that are difficult for attackers to penetrate. 72% of respondents to the second annual Oracle and KPMG Cloud Threat Report 2019 feel the public cloud is more secure than what they can deliver in their own data center and are moving their data to the cloud. In fact, the most pressing aspect of cloud security and governance going forward is the potential for customers to cause security failures. Gartner predicts that by 2020, 95% of cloud security failures will be the customer’s fault.

Finally, the cloud data warehouse largely eliminates the risks endemic to the costly and time-consuming on-premises data warehouse paradigm. You don’t have to budget for and procure hardware and software. You trade in your budget line item for annual maintenance and support for a smaller subscription fee. In the cloud, the cost considerations that have traditionally preoccupied data warehouse teams—budgeting for planned and unplanned system upgrades—get drastically reduced. You still need to test, but the more costly development of new features and patches are someone else’s burden. For these reasons and more, on-premises data warehouse workloads will continue to shift to the cloud. According to MarketandMarkets, the data warehouse as a service market size is expected to grow from $1.2 billion in 2018 to $3.4 billion by 2023, at a CAGR of 23.8%.

Oracle, AST deliver on analytics & cloud data warehousing

With the introduction of the world’s first “self-driving” database, Oracle Autonomous Database Cloud, Oracle is revolutionizing how data is managed. This ground-breaking Oracle database technology automates management to deliver unprecedented availability, performance, and security—at a significantly lower cost.

Powered by Oracle Database 18c, the next generation of the industry-leading database, Oracle Autonomous Database Cloud offers total automation based on machine learning and eliminates human labor, human error, and manual tuning. The Autonomous Data Warehouse helps IT and businesses work together to meet the evolving needs of their business and support any key function of the organization. 

One incredibly powerful use of Autonomous Database’s capabilities is Oracle Autonomous Analytics Cloud (OAAC). Oracle Autonomous Data Warehouse, paired with the power of Oracle Analytics Cloud, enables fast access to a sophisticated set of analytics that empower businesses to quickly extract data insights and make critical decisions in real time.

OAAC supports any data type, source, and size, and is a unified platform that allows you to take in any data, easily store it, and rapidly process it to deliver valuable insights within your analytics layer. 

Oracle Analytics Cloud combines all analytics capabilities — including planning, predictive analytics, reporting, and business intelligence (BI) — in a single SaaS solution. Users can take advantage of a modern, intuitive user experience and save time by planning, analyzing, predicting, and collaborating in context. As a true SaaS solution, Oracle Analytics Cloud offers scalability, accommodating everything from small, nimble departmental deployments to global implementations.

Topping the list of the many significant benefits of advanced analytics are customer intimacy, faster, smarter decision-making, greater productivity, and sustained competitive advantage. However, the prerequisites to achieving big data analytics are formidable — from ensuring data quality and seamless systems integration, to securing customer data, to extending analytics throughout the enterprise, and incorporating the latest advances in machine learning, AI, and IoT.

For our part, the depth, breadth, and flexibility of AST’s Oracle-based BI/analytics solutions, combined with our extensive cloud expertise and systems integration capabilities, enables customers of all sizes and across diverse industries to embark upon or accelerate their cloud analytics journeys.

At AST, we are committed to helping our customers unlock the potential of their data, wherever it resides, and make better, faster, more-informed decisions throughout their organizations.

In working toward this goal with our customers, we leverage the latest cloud, mobile, and data visualization technologies, along with present and future Oracle-based BI and analytics solutions, and increasingly hybrid (on-premise + cloud) delivery models.

When it comes to meeting the analytics needs of our customers, AST’s overarching goal is three-fold: make analytics more affordable; make analytics more efficient and easier to use; and extend the reach of analytics to more business users throughout the enterprise.

Contact AST today to learn how our Oracle Cloud experts can help your organization unlock big value from today’s big data.